Introduction
“According to Forrester Research, American workers spend $404 billion annually, or 11% of all U.S. wages, looking for the information they need to do their jobs. Giving employees the right tools to stay afloat in a data and knowledge-driven workplace is imperative across the board.”[1]
With the world of digital data growing exponentially year on year, the above quote could just represent a mere drop in the ocean when accounting for the time workers spend looking for information. The next question is, once the information has been found, can it then actually be interpreted and understood within its original context and in the context required? Without adequate systems to deal with the data deluge, and efficient working
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However metadata can also be costly and time consuming, especially if the human element of inputting the information is the primary way of getting the data into the files. Automation of the population of metadata fields is desirable, and with new technologies this is achievable, however it should be ensured that the right information is going into an asset. If a user is searching for a specific thing, then the system should know that the result it returns is the right one, and often this can only be done by human intervention when adding metadata. To aid with this, certain machine readable metadata fields, such as technical information about a file, can be automated upon
ingestion to a DAM, however descriptive information can be much more subjective. This conceptual thought around the description of a file can limit its discovery, as can a lack of knowledge about it in terms of the individual populating any descriptive metadata fields. This is where prescribing to the thoughts of writers such as Bearman [5] around allowing users to describe records as they are the ones with the relevant knowledge, can be very useful, but depending upon the institutions workflow it may also be impractical. Whatever metadata scheme is used, it must be properly structured to ensure it aids discovery, and displays all the information relevant to both the file and the
1.1 Describe Systems and Procedures for Storing and Retrieving Information Collect documents to be filed, sort in to alphabetical, numerical or chronological order, find the relevant file and place the document inside after it’s divider, and return the file to its original place. Confidential files should be kept in a lockable cabinet and old documents should be shredded after the length of time outlined by the organisation. Electronic filing is similar but on the computer. It is important to name files so that they are easily recognisable by everyone who may need to access it. If the information is confidential it should be encrypted with a password to prevent unauthorised access.
Digital asset management systems (DAMS) include computer software and hardware systems that aid in the process of digital asset management. (Beal,2015). The Key to Social Media Success Within Organizations, Is always the right answer .
According to Lisa Arthur, big data is as powerful as a tsunami, but it’s a deluge that can be controlled. In a positive way it provides business insights and value. Big data is data that exceeds the processing capacity of conventional database systems. It is a collection of data from traditional and digital sources inside and outside a company that represents a source of ongoing discovery and analysis. The data is too big, moves to fast, or doesn’t fit the structures of the database architecture. Daily, we create 2.5 quintillion bytes of data. In the last couple years we have created 90% of data we have in the world. This data comes from many places like climate information, social media sites, pictures or videos, purchase transaction records, cell phone GPS signals, and many more places. From the beginning of recorded time through 2003 users created 5 billion gigabytes of data. 2011, the same amount was created every couple days. 2013, we created that same amount every ten minutes. Some users prefer to constrain big data into digital inputs like web behavior and social network interactions. The data doesn’t exclude traditional data that is from product transaction information, financial records and interaction channels.
Setia, P, Venkatesh, V, &Joglekar, S (2013).'LEVERAGING DIGITAL TECHNOLOGIES: HOW INFORMATION QUALITY LEADS TO LOCALIZED CAPABILITIES AND CUSTOMER
Key Internet Cases (2002) Significant Internet Jurisdiction Cases. Online at http://www.unc.edu Referecned on November 22nd, 2004
This strategy successfully persuaded older employees to adopt Box, a cloud-based storage platform for the company’s architectural drawings and financial documents. The organization’s adoption of the Box software grew out of a trial at one job site and just took off, caught fire, adoption-wise... And soon, what had started as a small group test grew intoalmost one hundred Box users within a few weeks. The reason for this growth was word-of-mouth testimonials that employees gave after using the software within the company. In addition to his cheerleader approach, Sarrubi also makes sure that working with the new technology is “as easy as using Amazon.” Cost, scalability, and return-on-investment are important factors the company considers when making IT decisions, but end-user preference is also a big factor in what technologies the company
Upshaw, D., & Babin, L. A. (2010). Music downloading: Competing against online piracy. International Journal of Business & Public Administration, 7(1), 14-26. Retrieved from EBSCOhost
Grossman, Lawrence K. The Shape of the Electronic Republic. Composing Cyberspace. Richard Holeton. United States: McGraw-Hill, 1998, 311-327.
Turban, E. (2009) Information technology for management : transforming organizations in the digital economy. 7th ed. Hoboken: John Wiley & Sons Inc.
Teachout, Terry. “Copyright Protection That Serves to Destroy.” Wall Street Journal. 15 Mar. 2013: D.6. SIRS Issues Researcher. Web. 21 Jan. 2014.
"Although fully searchable text could, in theory, be retrieved without much metadata in the future, it is hard to imagine how a complex or multimedia digital object that goes into storage of any kind could ever survive, let alone be discovered and used, if it were not accompanied by good metadata" (Abby Smith). Discuss Smith's assertion in the context of the contemporary information environment
Register, R. (2013). The importance of metadata for E-content. EContent Quarterly, 1(1), 30-44. Retrieved from http://search.proquest.com/docview/1467943727?accountid=10043
But what good is all this information if it is not usable? "Almost all our resources are dedicated to gathering the raw material--information--and almost nothing is spent on the most important job of transforming information into intelligence" (Milton 1989, p. 6). Milton suggests that it is possible to have "negative information"--that which causes the recipient to know less than before because it is not integrated, applied, and transformed into knowledge. Essential to information mastery is understanding the relationship between data, information, and knowledge (TAFE-TEQ 1992): data are raw facts and figures, information is data organized into a meaningful context, and knowledge is organized data (i.e., information) that has been understood and applied.
Daniel Bell (1973) coined the expression ‘the post-industrial society’. In this society a substantial proportion of the population are employed or involved in the work of information collection and communication. In this sense we can see that information has become a commodity which can have a value and is therefore marketable. It also can be seen as an indispensable component of our social fabric.
Boepple, Paul. "Internet." The New Book of Knowledge. 34th ed. 20 vols. Chicago: Grolier Inc., 2000.